目的 探讨中医药治疗小儿腺样体肥大（AH）的研究现状、研究热点及趋势,为本领域研究者提供借鉴。方法 检索中国知网（CNKI）数据库从2005年1月1日至2024年1月31日中医药治疗小儿腺样体肥大的相关文献。运用Excel 2019分析其发文量,运用CiteSpace 6.2.R6软件分析其作者、机构、关键词。结果 共纳入文献395篇,年发文量整体呈现波动上升的趋势;发文量最多的作者为姜之炎;发文量最多的研究机构为山东中医药大学。初步形成了以姜之炎、俞景茂、阎兆君为核心的研究团队;研究机构以中医类院校及其附属医院为主。高频关键词提示当前研究热点前三位为中医药治疗方法、临床疗效。结论 AH领域研究内容主要以内治法、外治法、作用机制为主;研究热点逐渐从临床研究转向作用机制等实验研究;应用“数据挖掘”“网络药理学”等计算机技术研究AH会成为趋势。
Objective To explore the research status,research hotspots,and trends of traditional Chinese medicine in the treatment of adenoid hypertrophy in children,to provide a reference for researchers in this field．Methods The relevant literature on the treatment of adenoid hypertrophy in children with traditional Chinese medicine was searched in the CNKI database from January 1,2005,to January 31,2024．Excel 2019 was applied to analyze the number of published papers,and CiteSpace 6.2.R6 software was applied to analyze its authors,institutions,and keywords．Results A total of 395 papers were included,and the annual number of papers showed a fluctuating upward trend．The author with the largest number of papers was JIANG Zhiyan．Shandong University of Traditional Chinese Medicine was the research institution with the largest number of papers．The core research teams including JIANG Zhiyan,YU Jingmao,and YAN Zhaojun were initially formed．The research institutions were mainly Chinese medicine colleges and their affiliated hospitals．High-frequency keywords suggest that the current top three research hotspots were traditional Chinese medicine treatment methods,clinical efficacy．Conclusions The research content in this field is mainly based on internal treatment,external treatment,and mechanism．The focus has gradually shifted from clinical research to experimental research such as mechanism．The application of computer technologies such as “data mining” and “network pharmacology” for this disease will become a trend．
目的 本研究观察应用鼻喷激素联合白三烯受体拮抗剂在腺样体肥大患儿中治疗的效果。方法 选择2016年2月—2018年3月期间在广州市某区妇幼保健院耳鼻咽喉科确诊腺样体肥大的患儿,在患儿及家长知情同意的基础上,按照随机数字表法将87例耳鼻咽喉科诊断为腺样体肥大的儿童分为研究组和对照组。前者给予鼻喷激素联合白三烯受体拮抗剂进行治疗,后者独立使用白三烯受体拮抗剂进行治疗,比较两组患儿的临床治疗效果和不适症状的改善程度。结果 研究组腺样体肥大患儿临床症状得分小于对照组,优于对照组的治疗效果,差异有统计学意义(P＜0.05);且对比对照组,研究组患儿经鼻呼吸困难、入睡时打鼾、鼻部阻塞感等不适症状明显减轻。结论 鼻喷激素联合白三烯受体拮抗剂治疗儿童腺样体肥大,临床症状改善较为明显,具有经济性,家属及患儿接受度较高,相比手术创伤小,在基层医院推广有一定的价值。
目的 探讨中医药治疗小儿腺样体肥大（AH）的研究现状、研究热点及趋势，为本领域研究者提供借鉴。方法 检索中国知网（CNKI）数据库从2005年1月1日至2024年1月31日中医药治疗小儿腺样体肥大的相关文献。运用Excel 2019分析其发文量，运用CiteSpace 6.2.R6软件分析其作者、机构、关键词。结果 共纳入文献395篇，年发文量整体呈现波动上升的趋势；发文量最多的作者为姜之炎；发文量最多的研究机构为山东中医药大学。初步形成了以姜之炎、俞景茂、阎兆君为核心的研究团队；研究机构以中医类院校及其附属医院为主。高频关键词提示当前研究热点前三位为中医药治疗方法、临床疗效。结论 AH领域研究内容主要以内治法、外治法、作用机制为主；研究热点逐渐从临床研究转向作用机制等实验研究；应用“数据挖掘”“网络药理学”等计算机技术研究AH会成为趋势。
Objective To explore the research status，research hotspots，and trends of traditional Chinese medicine in the treatment of adenoid hypertrophy in children，to provide a reference for researchers in this field．Methods The relevant literature on the treatment of adenoid hypertrophy in children with traditional Chinese medicine was searched in the CNKI database from January 1，2005，to January 31，2024．Excel 2019 was applied to analyze the number of published papers，and CiteSpace 6.2.R6 software was applied to analyze its authors，institutions，and keywords．Results A total of 395 papers were included，and the annual number of papers showed a fluctuating upward trend．The author with the largest number of papers was JIANG Zhiyan．Shandong University of Traditional Chinese Medicine was the research institution with the largest number of papers．The core research teams including JIANG Zhiyan，YU Jingmao，and YAN Zhaojun were initially formed．The research institutions were mainly Chinese medicine colleges and their affiliated hospitals．High-frequency keywords suggest that the current top three research hotspots were traditional Chinese medicine treatment methods，clinical efficacy．Conclusions The research content in this field is mainly based on internal treatment，external treatment，and mechanism．The focus has gradually shifted from clinical research to experimental research such as mechanism．The application of computer technologies such as “data mining” and “network pharmacology” for this disease will become a trend．
